PySide6Pandas

    PySide6Pandas is a Python module that contains classes for extending Pandas to integrate with PySide6, based off of PyQt5Pandas. It provides utilities to use Pandas DataFrames in PySide6 applications, including custom table models for displaying and editing data in QTableView, as well as dialogs for importing data from CSV files and other formats.
    
    ## Features
    
    - **Pandas DataFrame Integration**: Custom QAbstractTableModel implementations for seamless display of Pandas DataFrames in PySide6's QTableView.
    - **Editable Views**: Support for editing DataFrame cells directly in the GUI, with changes reflected back to the underlying DataFrame.
    - **Data Import Dialogs**: Dialogs like CSVImportDialog for loading data into DataFrames from files.
    - **Sorting and Filtering**: Built-in support for sorting columns and filtering rows within the view.
    - **Extensible Classes**: Easily subclass models and views for custom behaviors.
    - **Cross-Platform Compatibility**: Works on Windows, macOS, and Linux with PySide6.
    - **Performance Optimized**: Efficient handling of large DataFrames with lazy loading and virtualization.
    
    ## Installation
    
    You can install PySide6Pandas via pip:
    
    ```bash
    pip install pyside6pandas
    ```
    
    Alternatively, clone the repository and install from source:
    
    ```bash
    git clone https://github.com/<USER_OR_ORG>/pyside6pandas.git
    cd pyside6pandas
    pip install -e .
    ```
    
    ### Requirements
    
    - Python 3.<MIN_VERSION> or higher
    - Dependencies: pyside6, pandas (automatically installed via pip where applicable)
    
    ## Quick Start
    
    Import the module, create a DataFrameModel, and display it in a QTableView:
    
    ```python
    import sys
    from PySide6.QtWidgets import QApplication, QTableView
    import pandas as pd
    from pyside6pandas.models import DataFrameModel
    
    app = QApplication(sys.argv)
    
    df = pd.DataFrame({'Name': ['Alice', 'Bob'], 'Age': [30, 25]})
    model = DataFrameModel(df)
    view = QTableView()
    view.setModel(model)
    view.show()
    
    sys.exit(app.exec())
    ```
    
    ## Usage
    
    ### Creating a DataFrameModel
    
    The core class is DataFrameModel, which extends QAbstractTableModel:
    
    ```python
    from pyside6pandas.models import DataFrameModel
    
    df = pd.DataFrame(data=[[1, 2], [3, 4]], columns=['Col1', 'Col2'])
    model = DataFrameModel(df, editable=True)
    # Use model with QTableView
    ```
    
    ### Using Data Import Dialogs
    
    Import data via dialogs:
    
    ```python
    from pyside6pandas.views import CSVImportDialog
    
    dialog = CSVImportDialog()
    if dialog.exec():
        df = dialog.getDataFrame()
        # Use the imported DataFrame
    ```
    
    ### Advanced Views
    
    Extend or use provided views for additional functionality:
    
    ```python
    from pyside6pandas.views import DataFrameView
    
    view = DataFrameView()
    view.setDataFrame(df)
    view.show()
    ```
    
    ## Examples
    
    ### Example 1: Basic DataFrame Display
    
    ```python
    import sys
    from PySide6.QtWidgets import QApplication, QMainWindow
    import pandas as pd
    from pyside6pandas.models import DataFrameModel
    from pyside6pandas.views import DataFrameView
    
    app = QApplication(sys.argv)
    window = QMainWindow()
    
    df = pd.read_csv('data.csv')
    view = DataFrameView()
    view.setDataFrame(df)
    window.setCentralWidget(view)
    window.show()
    
    sys.exit(app.exec())
    ```
    
    ### Example 2: Editable DataFrame with Saving
    
    ```python
    import sys
    from PySide6.QtWidgets import QApplication, QTableView, QPushButton, QVBoxLayout, QWidget
    import pandas as pd
    from pyside6pandas.models import DataFrameModel
    
    app = QApplication(sys.argv)
    
    df = pd.DataFrame({'Item': ['A', 'B'], 'Price': [10.5, 20.0]})
    model = DataFrameModel(df, editable=True)
    view = QTableView()
    view.setModel(model)
    
    save_button = QPushButton('Save Changes')
    save_button.clicked.connect(lambda: df.to_csv('updated.csv'))
    
    layout = QVBoxLayout()
    layout.addWidget(view)
    layout.addWidget(save_button)
    widget = QWidget()
    widget.setLayout(layout)
    widget.show()
    
    sys.exit(app.exec())
    ```
    
    ## Configuration Guide
    
    Customize models with options like:
    
    - `editable`: Boolean to enable editing (default: False)
    - `sortable`: Boolean to enable column sorting (default: True)
    - `custom_formatters`: Dictionary for column-specific formatting
    
    For advanced customization, refer to the [docs/config-reference.md](docs/config-reference.md).
    
    ## Contributing
    
    Contributions are welcome! Please follow these steps:
    
    1. Fork the repository.
    2. Create a feature branch (`git checkout -b feature/<FEATURE_NAME>`).
    3. Commit your changes (`git commit -am 'Add some feature'`).
    4. Push to the branch (`git push origin feature/<FEATURE_NAME>`).
    5. Open a Pull Request.
    
    See [CONTRIBUTING.md](CONTRIBUTING.md) for more details.
    
    ## License
    
    This project is licensed under the <LICENSE_TYPE> License - see the [LICENSE](LICENSE) file for details.
    
    ## Acknowledgments
    
    - Based on the concepts from PyQt5Pandas for PyQt5 integration.
    - Thanks to contributors of underlying libraries like PySide6, pandas.